Comparative Analysis of Neural Network and Machine Learning Models for Short-Term Traffic Flow Prediction on Shenzhen Expressway | Topilin | Advanced Engineering Research (Rostov-on-Don)

Advanced Engineering Research (Rostov-on-Don)

ISSN 2687-1653 (Online)

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Topilin I.V., Han M., Feofilova A.A., Beskopylny N.A. Comparative Analysis of Neural Network and Machine Learning Models for Short-Term Traffic Flow Prediction on Shenzhen Expressway. Advanced Engineering Research (Rostov-on-Don). 2025;25(4):350-362. https://doi.org/10.23947/2687-1653-2025-25-4-2215. EDN: DWKVUM

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About the Authors

I. V. Topilin
Don State Technical University
Russian Federation

Ivan V. Topilin, Cand.Sci. (Eng.), Associate Professor of the Department of Organization of Transportation and Road Traffic Management

1, Gagarin Sq., Rostov-on-Don, 344003

Scopus Author ID: 57193746467

M. Han
Don State Technical University
Russian Federation

Mengyi Han, Postgraduate student of the Department of Organization of Transportation and Road Traffic Management

1, Gagarin Sq., Rostov-on-Don, 344003

A. A. Feofilova
Don State Technical University
Russian Federation

Anastasia A. Feofilova, Cand.Sci. (Eng.), Associate Professor of the Department of Organization of Transportation and Road Traffic Management

1, Gagarin Sq., Rostov-on-Don, 344003

Scopus Author ID: 57193742031

N. A. Beskopylny
Don State Technical University
Russian Federation

Nikita A. Beskopylny, Postgraduate student of the Department of Organization of Transportation and Road Traffic Management

1, Gagarin Sq., Rostov-on-Don, 344003

Scopus ID: 57221328153

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Advanced Engineering Research (Rostov-on-Don)

ISSN 2687-1653 (Online)

Contact with: Publisher / Editorial Office of the Journal

Publisher: Don State Technical University - DSTU, Rostov-on-Don, Russia - https://donstu.ru/en/

Editor-in-Chief: Alexey N. Beskopylny, Dr.Sci. (Eng.), Professor, Vice-Rector, Don State Technical University (Rostov-on-Don, Russia)

Don State Technical University
1, Gagarin Sq., Rostov-on-Don, 344003, Russia
tel.: +7 (863) 2738-372, e-mail: vestnik@donstu.ru

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